An improved interval multi-objective programming model for irrigation water allocation by considering energy consumption under multiple uncertainties

Ren, Chongfeng; Xie, Zhishuai; Zhang, Yu; Wei, Xing; Wang, Yashi; Sun, Dengyue

doi:10.1016/j.jhydrol.2021.126699

Cited by 36 publications

(2 citation statements)

References 48 publications

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“…In reality, the water resource optimization system is complex and changeable, and the values of some parameters cannot be determined, which are expressed in the form of fuzzy numbers. (Ren et al 2021;Li et al 2020c;Huang et al 1993). Therefore, in order to deal with fuzzy problems, membership function was adopted, which has the ability to convert the fuzzy numbers to interval numbers.…”

Section: Fuzzy Setsmentioning

confidence: 99%

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An improved fuzzy multi-objective nonlinear programming model integrate PSO for water resources optimization allocation under uncertainties

Ren

Xie

Zhang

et al. 2022

Preprint

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The shortage of water resources has become one of the main factors restricting the development of society, and the impact of the shortage of water resources is particularly obvious in Northwest China in recent years. This paper establishes an inexact fuzzy non-linear multi-objective programming model aiming at the maximum economic benefit and maximum water productivity, which is applied to the actual case of Minqin, Gansu in Northwest China. Improved particle swarm optimization (PSO) is introduced to solve the model, and the optimization scheme of agricultural water resources allocation in the study area is obtained under multiple uncertainties. The results show that the optimization of multi-objective model by IPSO can comprehensively adjust the economic benefits and water productivity. The upper limit of economic benefits can reach 8.84×108 ¥, and the water productivity is 6.29 ¥/m3, which improves the utilization efficiency of water resources and ensures the local economic benefits. The water resources allocation scheme obtained by the multi-objective optimization model can not only provide potential scenarios for local water resources decision-makers, but also provide a reference for the optimal allocation of agricultural water resources in similar areas.

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Section: Fuzzy Setsmentioning

confidence: 99%

“…At present, water resources have become the main factor restricting human social and economic development because of drought and climate change (Qian et al 2021;Gong et al 2020;Abedin et al 2019). With the rapid growth of the world population, the water resources crisis is becoming more and more serious (Ren et al 2021;Li. 2021b).…”

Section: Introductionmentioning

confidence: 99%

An improved fuzzy multi-objective nonlinear programming model integrate PSO for water resources optimization allocation under uncertainties

Ren

Xie

Zhang

et al. 2022

Preprint

Self Cite

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Uncertain multi‐objective programming approach for planning supplementary irrigation areas in rainfed agricultural regions

Shi,

Han,

Guo

2024

Irrigation and Drainage

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Rainfed agriculture is crucial for ensuring global food and water security, and supplementary irrigation is an effective means of improving the economic benefits in rainfed agricultural regions. This study proposes a novel uncertain optimization approach to optimize supplementary irrigation areas in rainfed agricultural regions. The approach incorporates multi‐objective linear programming, interval linear programming, fuzzy goal programming and stochastic expected value programming. In the proposed interval multi‐fuzzy goal stochastic expected‐value programming, uncertainties are expressed in the form of discrete intervals, probability distributions and fuzzy goals. This approach, which considers the randomness of precipitation during the optimization process and allocates limited irrigation water resources to different subareas and crops, was applied to a case study of crop irrigation area planning in Guyuan City, Ningxia Hui Autonomous Region, northwestern China. The maximum economic benefits and the minimum sum of the Gini coefficients among the different subareas and crops were regarded as the planning objectives, and a series of optimal irrigation areas with different crops and subareas under different water levels were obtained. The optimization results revealed that vegetables and fruits consumed large amounts of irrigation water to increase their economic benefits. In addition, allocating a large amount of irrigation water to wheat is essential to decrease the Gini coefficient and meet food security constraints, particularly at extremely low water levels. Compared with current management, the optimized irrigation area decreased by 30%, the crop water deficit index increased by 9%, the economic benefits increased by 3% and the total Gini coefficient of crops decreased by 17%, indicating that the optimization approach could fairly and reasonably allocate irrigation water resources. Our research provides a mathematical approach for decision‐makers to plan supplementary irrigation areas in rainfed agricultural regions.

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An irrigation scheduling algorithm for sustainable energy consumption in pressurised irrigation networks supplied by photovoltaic modules

Navarro-González

Pardo

Chabour

et al. 2023

Clean Techn Environ Policy

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To meet water demands, pressurised irrigation networks often need pumping devices, whose power demand varies with the pump head, the flow rate delivered and the pump efficiency. To satisfy the energy demand of pumps, solar photovoltaic panels can be used as a renewable energy source. Since the electricity supply of a solar photovoltaics plant depends on irradiance, the energy that powers the pump varies with the time of the day. This study presents a strategy for scheduling water delivery by irrigation pumps, synchronising energy production in solar photovoltaic modules and minimising the installation size. An optimisation algorithm is proposed, which changes the energy required by pumping devices and adjusts them to the available solar energy supply, minimising the number of panels required. This problem applies to a pressurised irrigation network, where the utility manager may irrigate crops at all hours of the day. By adopting the proposed algorithm, irrigation will follow a rigid rotation schedule to follow the new irrigation plan. This approach improves earlier studies by employing a least-square scheduling algorithm with little computing time. This results in a tool for managers and decision-makers when evaluating the possibility of converting their irrigation network into a stand-alone system supplied by photovoltaic panels. A case study handling this issue in the University of Alicante’s pressurised irrigation network in Spain is proposed to find potential energy savings by connecting the recommended scheduling irrigating plan to the present operation. Graphical abstract

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An improved interval multi-objective programming model for irrigation water allocation by considering energy consumption under multiple uncertainties

Cited by 36 publications

References 48 publications

An improved fuzzy multi-objective nonlinear programming model integrate PSO for water resources optimization allocation under uncertainties

An improved fuzzy multi-objective nonlinear programming model integrate PSO for water resources optimization allocation under uncertainties

Uncertain multi‐objective programming approach for planning supplementary irrigation areas in rainfed agricultural regions

An irrigation scheduling algorithm for sustainable energy consumption in pressurised irrigation networks supplied by photovoltaic modules

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